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This paper identifies and models the effect of eight attributes that influence hotel room rents in India. These attributes are conceptually grouped into three factors: (1) site factors including the presence or absence of a “swimming pool,” “free breakfast,” and the “hotel capacity”; (2) situational factors including, “distance from the airport,” “weekend/weekday,” “city population,” “cost of living”; and (3) a reputation factor indicated by “star rating.” Our regression model uses secondary data collected from a hotel booking website for 570 hotels across 18 cities of India. The results indicate that six out of these eight variables namely, presence of swimming pool, free breakfast, hotel capacity, distance from the airport, city population, and hotel star rating have a significant impact on hotel room rents in India.

The purpose of this study is to examine the influence of key hotel attributes on the room rates of selected hotels in the Greater Gaborone Region, Botswana.

Using hedonic pricing analysis, the effect of eight attributes collected from 80 standard double rooms on Booking.com in the area was analysed using quantile regression.

The estimated results from quantile regression suggested the importance of the 10th quantile as the best predictor of hotel room price distribution. Overall, the presence of a fitness centre and the availability of meeting and conference facilities were positively significant for the lowest- and premium-priced hotels, respectively.

The study advanced the literature in hedonic pricing models by confirming the applicability of hotel room rate attribute research in unexplored environments.

Hotel managers should be aware of the influence of key attributes, such as meeting and conference space availability and locational factors, on the pricing decisions of room rates in the Greater Gaborone Region. The study also presented opportunities for business-to-business marketing between hotel and tour operators in the region.

The study is one of the few that uses quantile regression in the hedonic pricing analysis of hotel room rates.

The purpose of this paper is to analyze the implicit prices of hotel attributes in different time periods and different markets.

With data from the travel meta-search engine, this paper chose 3- to 5-star hotels in Beijing’s central business district and use hedonic price models.

The results suggest that the attributes with significant implicit prices differ in different time periods; the same attributes with different implicit prices in different time periods; the same attributes with different implicit prices in different market segments.

This study may help to explain the different findings on the relationship between the attributes and room rates of Chinese star-rated hotels in different time periods, and will be useful in both revenue optimization efforts and the design of new hotels projects.

This paper aims to develop overbooking models to determine the optimal number of overbooking for hotels having one and two different types of rooms.

This paper presents mathematical modeling to find the optimal solutions of overbooking for stochastic cancellation.

The authors prove that for hotels with only one type of room, there exists a closed form solution to guarantee the optimal number of overbooking, depending on the cost of walking customers to other hotels, the cost of unsold rooms and cancellation distribution observed in the past. For hotels with two types of room, they prove the convexity structure and identify equations to seek the number of overbooking for low-price and high-price rooms. The authors also provide key comparative statics on how model parameters impact the optimal decisions under different scenarios.

Overbooking decision is one of important and complicated decision-makings, which is related directly to the yield of hotel revenue management. It is necessary for a hotel manager to observe cancellation pattern in the history to make a reliable decision. This paper presents a method that can help hotel manager make this decision in practice.

This paper is one of the first articles in the hotel industry that considers the marginal cost for each room unsold caused by no shows and the marginal cost for each walking guest in a comprehensive perspective.

This study aims to examine whether and how hotel class, attributes of the room, quality, location, cleanliness, and service influence room rates in hotels.

Regression models were developed for the hotel industry and for various grades of hotels.

Using data from New York, empirical findings suggest that room quality and location are important determinants of room price for the industry, but attributes that can influence room rates differ greatly among hotel segments.

Hotels can reap benefits from understanding customers' specific expectation of a market segment and seeking to provide amenities accordingly.

The quality of hotel attributes is evidenced through customer reviews on a travel advice website. The theory of the hierarchy of needs is supported in the hotel industry, namely, the ascending order of accommodation needs are the quality of a room, location, and service.

Online ratings (review valence) have been found to exert a strong influence on hotel room prices. This study aims to systematically synthesize research estimating the impact of online ratings on room rates using a meta-analytical method.

From major academic databases, a total of 163 estimates of the effects of online ratings on room rates were coded from 22 studies across different countries through a systematic review of relevant literature. All estimates were converted into elasticity-type effect sizes, and a hierarchical linear meta-regression was used to investigate factors explaining variations in the effect sizes.

The median elasticity of online ratings on hotel room rates was estimated to be 0.851. Meta-regression results highlighted four categories of factors moderating the size of this elasticity: data characteristics, research settings, variable measures and publication outlet. Among sub-ratings, results revealed value rating and room rating to exert the largest impact on room rates, whereas staff and cleanliness ratings demonstrated non-significant impacts.

This study provides practical implications on the relative importance of different types of online ratings for online reputation and revenue management.

This study represents the first research effort to understand factors moderating the effects of online ratings on hotel room rates based on a quantitative review of the literature. Moreover, this study provides beneficial insights into the specification of empirical hedonic pricing models and data-collection strategies, such as the selection of price variables and choices of model functional forms.

The internet has significantly changed the ways hotels distribute and price their products. The imminent success of online intermediaries caused financial problems for hotel chains since online travel agencies offered better prices than the hotel brand websites. The existing literature on hotel online distribution has focused on pricing strategies and room availability issues for different segments of hotels. This paper, however, aims to compare online room prices of global hotel chains across online distribution channels and their own brand websites.

By using only the internet, 2,800 room rates were collected and analyzed. Descriptive statistics such as means and percentage were used to answer the research questions. Personal interviews with a CEO of an e‐business company and an area revenue director of a global hotel chain were conducted to confirm our findings and to gain additional insights in the related issues.

Descriptive statistics indicated that US properties are doing a much better job than their international partners in regards to “best rate guarantee,” “rate parity,” and room availability across online channels. Rate consistency still remains a problem within US properties.

A limitation of this study is the use of convenience sampling methods, sample size, and currency conversion instruments.

Findings of this study would benefit revenue managers, general managers, hotel owners, and corporate brand managers to make decisions and to formulate new policies concerning their online distribution, revenue, and brand optimization strategies.

This study aims to measure the effect on prices through the differing characteristics and attributes of hotels.

A hedonic price model (HPM) was adopted to estimate the impact of various site and situational factors on hotel prices in Warsaw, Poland. To better understand room rates not explained by HPM, spatial analysis of residuals was used. Datasets regarding prices from three different online travel agents (OTAs) and star ratings, either official or provided by OTAs, were investigated.

A significant impact on hotel prices by star rating has been confirmed. Every additional star allows the hotel to set approximately 25 to 36 per cent higher prices, which is in line with previous studies. Moreover, two factors indicated a high but still underestimated theoretical hotel prices: location within the city centre and proximity to the international airport.

The results of this study suggest that hoteliers should use a spatial analysis of room rates offered by the competing enterprises. Moreover, managers are expected to verify their price tactics and policies according to the geographical determinants of hotel prices investigated.

The uniqueness of the study is highlighted by comparison of HPMs based on data from different OTAs, analysing differences in HPMs based on star ratings provided by OTAs and official systems and spatial analysis of residuals of estimated HPMs. Moreover, this study is among the first to examine the usage of HPM in the hospitality industry in East-Central Europe.

For more than 40 years, researchers have examined an exhaustive set of attributes as price determinants in tourism and hospitality. In extending this rich research stream, this study aims to propose and empirically assess a new set of hotel attributes, namely, faith-based attributes that allow tourists to continue following the activities and rituals guided by their religions while on vacation.

Using the Bayesian quantile regression for the first time in the field of hotel pricing, the hedonic pricing models examine both internal and external faith-based attributes, namely, halal services, which cater to the needs of Muslim tourists, in a sample of 805 hotels across the top three non-Muslim country destinations (Singapore, Thailand and Japan).

By exploring the effects of faith-based (halal) attributes available in hotels located in the biggest cities of the above-mentioned destinations, this study provides evidence for the significant role of faith-based (halal) attributes in determining hospitality prices.

This study’s findings offer a resource for several implications for tourism and hospitality scholars, practitioners and policymakers, especially within the field of Muslim/halal tourism, to develop action plans and strategies.

This study is the first to introduce a novel set of faith-based hospitality attributes and empirically assess their impact on hospitality price formation. Additionally, it contributes to the hedonic pricing method by being the first to use the Bayesian quantile regression.

This research aims to reveal that accessibility of hotels to major points of attraction in the urban–territorial continuum of Catalonia, with its urban and coastal landscapes, has a direct impact on the dependent variables of customer satisfaction and average room rate.

The study collected data from 84 of 4-star hotel establishments, divided into urban and coastal hotels. Both coastal and urban hotels were differentiated depending on their distance to, the beach and the urban city center, respectively. Customer satisfaction and average room rate data were retrieved from online review platforms.

The study proves that hotels located in the urban–territorial continuum of Catalonia have different behaviors in terms of customer satisfaction and hotel pricing according to the variables of distance and landscape. The study shows that room rate and customer satisfaction are both higher in urban landscapes than in coastal landscapes. Urban hotels present significant differences in their levels of customer satisfaction and room rates depending on their location in the city of Barcelona. However, coastal hotels do not represent significant differences in room rates depending on their location, although they do represent significant differences in terms of customer satisfaction.

The originality of this study is based on how a dynamic urban–territorial model consisting of Barcelona and the Maresme coast, the hotel location and distances to main interest points impact in the variables of customer satisfaction and average room rate.